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Abstract
Prior research has investigated the information content of credit ratings for standard financing instruments such as stocks and corporate bonds, while this question has been neglected for convertible bonds (CBs) so far. CBs are simultaneously determined by the bond floor and the conversion value, which makes it more difficult to assess price effects following rating announcements. In this context, we compare price effects of CBs with those of stocks and corporate bonds of the same issuer using robust event study methods. Our findings indicate that rating changes convey new information for investors in European CBs. In terms of the direction of the expected price reaction, we find CBs to react in a more debt-like manner to the announcement of a rating change. Moreover, our results provide evidence that the magnitude of price reactions differs among different types of securities.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1. The number of CB issuances p.a. globally increased by 26.7% during the same period.
2. Rating agencies prefer a “rating-through-the-cycle’ approach (see e.g. Löffler (Citation2004), and the contributions to issue 11/2004 of the JoBF) meaning that they abstain from rating adjustments if they value an alteration of creditworthiness as minor or/and temporary.
3. We only include CBs that can be transformed into stocks of the same issuer.
4. The issuer rating equals the issue rating for the corporate bonds investigated. The CBs in the sample are mostly rated one notch lower compared to the issuer rating and the issue rating for corporate bonds. However, for all the sample firms the rating changes for the issuer rating as well as for both types of issue rating are announced at the same date.
5. For stocks and corporate bonds, the distribution accounts for approx. 41.0% and 46.0%. This difference is mainly driven by multiple bond issuances affecting both bond samples.
6. We define periods of economic downturns according to the classification of the National Bureau of Economic Research. Consequently, downturns include rating changes during the years 2001 and 2002 (new economy crisis) as well as 2007–2010 (subprime crisis).
7. Between 2000 and 2010, 70.6% of all negative rating changes on European markets were announced during the new economy crisis and the subprime crisis. In contrast, 68.5% of all upgrades were announced between the years 2003 and 2006 (sources: corporate default studies and rating transitions of Fitch, Moody’s, and S & P’s).
8. We control for the subordination status by using the ‘Deal Type Description’ of the Thomson Reuters Eikon database. The average initial maturity of the corporate bonds of our sample is 10.9 years. The difference is caused by multiple bond issues, which are included in both bond samples.
9. As a part of Thomson Reuters Eikon, CreditViews is a specific database for company information concerning credit risk.
10. Besides these keywords, the authors applied additional ones such as ‘Financial Metrics’, ‘Event Risk’, ‘New Methodology’, and ‘No Rationale’. We did not describe these keywords because they do not serve as reasons for rating changes in our sample.
11. 22.6% of prior studies used an estimation period of 100 trading days. A list of prior studies used for this calculation is available from the authors on demand.
12. According to Rousseeuw (Citation1984), the breakdown value refers to the maximum percentage of outliers which is acceptable and does not result in a complete failure of the regression model. The breakdown value of the OLS regression is 0%, implying that the existence of a single outlier would lead to the total failure of the regression model whereas the robust regression method causes a breakdown value up to 50%.
13. The average R2 of stocks (corporate bonds) increases by approx. 8.13% (18.82%). The authors can provide the results of this descriptive statistics on demand.
14. In addition, Sorokina, Booth, and Thornton (Citation2013) recommend this window as being the most accurate, since it allows for detecting spillover effects in surrounding days and does not weaken the power of statistical tests in terms of confounding events.
15. Bootstraps are based on random samples drawn with replacement from the original sample, here the set of times series, and result in a population of random values of the test statistic. Thus, a single observation is typically included several times in the computation of the single test statistic.
16. The monetary financial institution (MFI) long-term interest rate, which refers to interest rates charged to households and non-financial corporations domiciled in Euro-area countries, rose from 4.93% p.a. in January 2007 to 5.43% p.a. in December 2008.
17. With a portion of 80.0% of the total trading volume in the European CB market, hedge funds are the dominant investor type during our period of investigation (source: Highbridge Capital Management, LLC).
18. The authors can provide the results of the Durbin–Wu–Hausman test on demand.